Advertisement

Advertisement

Expensive drones take flying lessons from cheaper stunt doubles

If a drone falls in the forest…

LHJB Photography/Getty

By Conor Gearin

Some of the best lessons come from the school of hard knocks. But some kit is too delicate or expensive to be subjected to this. So researchers have instead taught cheap, expendable drones to pass on their hard-won knowledge to their more precious peers. Getting robots to learn and share general concepts in this way could also make them better at independent decision-making.

Teaching an artificial intelligence to fly an expensive vehicle is risky, since it needs to know what both success and failure look like. “Let’s say you want to train it to fly a really big helicopter,” says Shreyansh Daftry at the Jet Propulsion Lab in Pasadena, California. “You need it to crash a lot to get it to learn what a crash is – but that’s often not possible.”

Not wanting to risk a new, expensive drone, Daftry and colleagues took a cheaper vehicle and piloted it through a forest, sometimes taking it between obstacles and sometimes crashing it. Trial and error let the robot figure out how to fly safely by itself.

Advertisement

The researchers then took the drone’s abilities and transferred them to their more expensive craft, which was immediately able to use the second-hand know-how to avoid flying into trees itself.

Dog-brained drones

The trick to passing on an ability that can be adapted to fresh situations lies in the way the first drone learns. Teaching an AI sometimes works like dog training – the robot gets a treat or a slap on the paw depending on its choices, says Nicholas Roy at the Massachusetts Institute of Technology.

But in this case, the drone first has to learn what’s a treat and what’s a slap – then it writes its own rules based on its experiences. “It’s trying to work out for itself what its own reward should be,” says Roy.

The upshot is that the initial drone picks up general-purpose rules. Rather than learning specifically that it should go left when it sees a brown patch – a tree, say – it learns that a brown patch is bad and must be avoided in any way possible.

The strategy should work for many kinds of robots, says Roy. Getting robots to pass on general concepts they have learned makes them much more independent, he says. “It’s a change in how we think robots should make decisions.”